US3RN-Pytorch

The code is for the work:

@article{ma2021deep,
  title={Deep Unfolding Network for Spatiospectral Image Super-Resolution},
  author={Qing Ma, Junjun Jiang, Xianming Liu, and Jiayi Ma},
  journal={IEEE Transactions on Computational Imaging},
  volume={},
  number={},
  pages={},
  year={2022},
}

Requirements

pytorch == 1.6.1

Dataset

To train and test on CAVE data set, you must first download the CAVE data set form http://www.cs.columbia.edu/CAVE/databases/multispectral/. Put all the training images and test images in their respective folders. You can also download the processed data from https://drive.google.com/drive/folders/1lwsNkmDFW81PvRGPWWBh-5wQDtF8XgQ5?usp=sharing

Train

python main.py --mode train

Test

python main.py --mode test --nEpochs 150